The positive correlation between the triglyceride glucose-body mass index and the presence and severity of early-onset coronary artery disease
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective The triglyceride glucose-body mass index (TyG-BMI) has emerged as a novel, comprehensive tool for evaluating insulin resistance and metabolic risk. We intend to determine the relationship between the TyG-BMI and early-onset coronary artery disease (CAD).Methods A retrospective case-control study was performed, which included a cohort of 2,356 participants. Binary logistic regression was utilized to estimate odds ratios (ORs) and 95% confidence intervals (CIs), while restricted cubic splines (RCS) were applied to assess potential nonlinear associations. The predictive accuracy was evaluated using receiver operating characteristic (ROC) curves.Results The TyG-BMI was significantly elevated and independently correlated with the presence of early-onset CAD (OR = 1.004, 95% CI: 1.002–1.007, p = 0.002). In comparison with the first quartile, the fourth quartile of the TyG-BMI index demonstrated an increased risk of early-onset CAD (OR = 1.84, 95% CI: 1.32–2.56, p < 0.001). A nonlinear relationship between the TyG-BMI and early-onset CAD was illustrated by an inverted L-shaped curve, as depicted by RCS. Additionally, the TyG-BMI index correlated positively with the number of diseased vessels and the Gensini score. ROC analysis revealed that the TyG-BMI (AUC = 0.673) was more effective in predicting early-onset CAD than either the TyG index (AUC = 0.625) or BMI alone (AUC = 0.656).Conclusions The TyG-BMI index is independently associated with the early-onset CAD and has demonstrated a significant correlation with the extent of coronary artery lesions. It may serve as a cost-effective and accessible tool for identifying individuals at higher risk.
Source: Annals of Medicine
Authors: Ru-Hua Liu, Jing Li, Zhi-Xiang Sun, Ting-Ting Zhou, Cong Zhao, Qing-Wu Tian, Jun-Jie Guo, Chao Xuan
Institutions: Affiliated Hospital of Qingdao University, Qingdao University
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,557
Awards: G200620384, G4862449954
OpenAlex ID: W4414549845
